Abstract
Background:Acute promyelocytic leukemia (APML) due to coagulopathies drives hematological distress in clinical practices. A targeted and timely offered treatment can be a benefitting tool for patients.Aims:Present study was conducted to introduce pre‐microscopic screening of patients with acute promyelocytic leukemia (APML) through research potential parameters generated by routine hematology analyzers during CBC analysis.Methods:Blood samples of controls and patients (APML and other hematological neoplasms) were analyzed on Sysmex XN‐1000. Peripheral blood film was examined for morphological diagnosis. CBC parameters and values for intensities of white blood cell's side, forward, and side florescence light scatter were recorded from analyzer software. Statistical and machine learning (unsupervised) tools were used to evaluate the predictive power of routine and research CBC parameters. Novel APML factor was derived from white blood cell and platelet count along mean value of neutrophil side fluorescence light (NE‐SFL) through logistic regression. At proposed cutoff value (‐2.011), APML factor was challenged for prediction of APML among present study cases.Results:Values for white blood cell (WBC), platelet, and NE‐SFL were exceptionally discriminative for APML 5.65, 29.5, and 54.4 respectively in comparison to non‐APML 7.96, 219, and 47.00 respectively cases. In combination, WBC and platelet count increased the predictive power of NE‐SFL when utilized in derivation of our proposed “APML factor”: ‐4.5070 + (0.049213 x NE‐SFL) + (‐0.017431 x PLT) + (‐0.0058366 x WBC). This factor gave robust impact in differentiation of APML with high values 0.935 and 0.985 for sensitivity and negative predictive power (NPP) respectively at cutoff of ‐2.011.Summary/Conclusion:Our proposed APML factor has strong potential to be incorporate/calculate and examine as part of CBC report for early prediction of APML.
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